Papers by Keyword: Heat Transfer Coefficient

Abstract: For the reliable numerical simulation and design of compound forging processes involving dissimilar materials, an accurate representation of thermal boundary conditions is essential. In particular, the heat transfer coefficient (HTC) at the interface of the workpiece and the die strongly influences temperature distribution, material flow, and interfacial integrity. Despite its significance, the HTC is frequently modelled as constant in finite element (FE) simulation due to the lack of experimental data for forging-relevant conditions. Therefore, this study presents an experimental–numerical methodology for determining load-dependent HTCs representative for compound forging. A specialised test setup was used to reproduce the thermal–mechanical boundary conditions of hot bulk forming, by inducing contact pressures both below and above the flow stress of the workpiece material. Temperature histories were recorded using embedded thermocouples and analysed through an inverse numerical approach based on a one-dimensional (1D) finite element (FE) model. The influence of contact pressure, heating atmosphere, and lubrication on the HTC was systematically investigated for a S235JR specimen temperature of 600 °C. The results demonstrate a major pressure dependency of the HTC, whilst increasing for higher contact pressures. Oxide formation and lubrication were shown to significantly affect heat transfer behaviour, particularly while heating under atmospheric conditions. The presented approach provides process-specific HTC data that can substantially improve the predictive capability of numerical simulations for compound forging applications.

Abstract: This paper investigates the thermal performance of a longitudinal trapezoidal fin using the Finite Volume Method, considering temperature-dependent thermal conductivity and heat transfer coefficient. The governing energy equation is developed by incorporating nonlinear thermal parameters and transforming these to dimensionless forms. The domain is discretized into control volumes and the energy balance is applied to each node to develop a system of algebraic equations. The effect of parameters like effectiveness factor, fin steepness, thermal conductivity and scale factor on temperature distribution is then studied. The results provide insights into optimizing fin geometry and thermal properties for efficient heat dissipation in engineering applications, while the temperature gradients along the fin length offers useful information for design. The Finite Volume Method ((FVM) proves advantageous in handling irregular geometries and conserving local balances. Overall, this comprehensive numerical approach enables accurate prediction of the intricate thermal response of longitudinal trapezoidal fins.

Abstract: This study investigates the potential of nanofluids in enhancing heat transfer performance in a 2D tube through a combination of computational fluid dynamics (CFD) simulations and experimental analysis. Nanofluids, which are suspensions of nanoparticles in base fluids, offer improved thermal conductivity compared to conventional coolants. The study employs computational fluid dynamics (CFD) simulations to replicate the experimental setup and parameters used by Mustafa Moraveji et al. The objective is to assess the heat transfer coefficient (h) and compare the results with experimental data. The computational analysis utilizes CFD simulations to study the flow of nanofluids through the 2D tube and evaluate the heat transfer coefficients at different axial locations. The results indicate that the addition of nanofluids to the base fluid leads to an increase in the heat transfer coefficient, suggesting enhanced heat transfer performance due to the presence of nanoparticles. The findings are compared with experimental data from previous studies to validate the simulations. The study contributes valuable insights into the heat transfer characteristics of nanofluids in a 2D tube and demonstrates their potential for improving heat transfer efficiency. Further research can focus on optimizing nanofluid compositions, investigating additional parameters, and exploring practical applications in heat exchange systems for enhanced thermal management.

Abstract: A four-pass cross-flow heat exchanger was developed and manufactured in this practical study for two types of tubes: smooth and triangular finned tubes. The length of the tube is 250 mm, for a smooth tube the inner and outer diameter (19, 21 mm), and (19, 21 and 24 mm) the inner, outer diameter and the fin root for the finned tube respectively. Water is used as a hot fluid inside the tubes and air is used as a cold fluid outside the tubes. Inlet hot fluid temperatures were 50, 60, 70, and 80 °C, with three air speeds (1, 2, and 3 m/s), and volumetric flow rate (2, 3, 4, and 5 l / min) held steady at 25 ° C. The finned tube outperformed the smooth tube in terms of heat transfer rate, heat transfer coefficient, total heat transfer coefficient, and effectiveness, according to the findings.

Abstract: The requirement for effective cooling of modern electrical and mechanical components has increased due to the desire for more compact and efficient designs. Thermal systems have used working fluids as a method for cooling systems for many years. However, technological improvements have dictated that working fluids must be more efficient for their applications. Researchers presented nanofluids as a possible solution for this issue, and they have gained a lot of attention due to their capability to enhance the heat transfer coefficient in miniaturized cooling or heating systems. The main purpose of this paper is to enhance the heat transfer coefficient in micro scales by encouraging the random motion of the particles in the nanofluid. This is accomplished by placing a nozzle between two micro-channels. The random motion of the particles is enhanced within the nozzle, increasing the heat transfer coefficient in the microchannel downstream as a result. In addition, the effects of characteristics of nanofluid are discussed briefly.

Abstract: The Heat Transfer Coefficient (HTC) in casting is critical input in numerical simulations. However, it depends on alloy composition, melt temperature, mold preheating temperature and local casting modulus, hence it is difficult to determine a priori. This work uses temperature measurements obtained by thermocouples during investment casting of a multiple section reference part. HTC was determined by three different methods: (a) analytical, formulating a detailed expression for the HTC in time steps for a one-dimensional approximation (b) inverse, following a well-known iterative algorithm proposed in literature and (c) "trial-and-error" simulation runs for different HTCs based on the judgment of the analyst. In conclusion, the analytical method proved to be fast, but yields very approximate HTC. The inverse method achieves accurate temperature evolution, but it might be unrealistic in physics terms. The trial-and-error method is flexible and may be accurate yet cumbersome and uncertain, unless automated, for instance through a Genetic Algorithm.

Abstract: In this study, the heat transfer coefficients of 7050 aluminum alloy under different water temperatures, polyalkylene glycol aqueous solution concentrations and quenching medium types are calculated by an iterative method, and the heat transfer coefficient of the aluminum alloy under different quenching medium parameters was compared and the difference was discussed in detail. The results show that with the increase of water temperature, the heat transfer coefficient of 7050 aluminum alloy gradually decreases; with the increase of polyalkylene glycol aqueous solution concentration, the heat transfer coefficient gradually decreases; the order of heat transfer capacity of quenching medium is disclosed among the studied medium types.

Abstract: Since conventional cooling systems with channels are not adequate to achieve a high aspect quality with a short cycle time, a better concept has to be used to control the fast variation of temperature in the mold, close to the injected part. Recently, with advanced manufacturing technologies like 3D-printing, rapid heat cycle molding are developing, using for example lattice structures as heat exchanger inside the mold. Our work proposes an experimental study to analyze the influence of four lattice structures that were specifically designed for this industrial application. An instrumented bench was developed at the laboratory scale, to test the thermal efficiency of the lattice. The material and geometry of the lattice structures were selected based on their thermomechanical properties and their efficiency as a heat-exchanger. The instrumentation of the bench consists in measuring the flow rate and the pressures in the fluid, and also the temperatures at various locations. This allows us to determine the performances of the lattice structure. The results show that the denser the lattice structure, the better, whether considering the mechanical resistance or the thermohydraulic performances. The key element to understand this phenomenon is the average velocity of the fluid flowing inside the lattice structure, accelerating when the porosity decreases and thus bringing a more intense heat exchange.

Abstract: The goal of this study is to improve the accuracy and the validity of the prediction of the heat transfer coefficient (HTC) throughout flow boiling of different water-based nanofluids in a horizontal tube by developing an artificial neural network model using Ag/water, Cu/water, CuO/water, Al₂O₃/water, and TiO₂/water nanofluids. The multiple layer perceptron (MLP) neural network was designed and trained by 354 experimental data points that were collected from the literature. Thermal conductivity of nanoparticle, mass flux, volumetric concentration, and heat flux were used to serve as input variables of the model. The heat transfer coefficient (HTC) was used as the output variable. Via the method of the trial-and error, MLP with 8 neurons in the hidden layer was attained as the optimal artificial neural network structure. This developed smart model is more accordant with the experimental data than the correlations of the literature. The accuracy of the developed smart model was validated by the value of mean squared error (MSE=0.042) and the value of determination coefficient (R²= 0.9992 ) for all data.

Abstract: In cold forging, the temperature difference between the workpiece and the tool is small and thus deformation analysis is rarely coupled with thermal analysis. However, the friction coefficient of zinc phosphate coating with metal soap has a large temperature dependence. Consideration of the effects of workpiece and tool temperature change on the friction coefficient is thus expected to improve the analytical accuracy of cold forging. Thermally coupled cold forging analysis requires thermal conductivity, specific heat, heat transfer coefficient between the workpiece and the tool, in addition to the temperature dependence of flow stress and friction coefficient. The heat transfer coefficient between workpieces coated with zinc phosphate with metal soap and tools is investigated in this paper. Cold backward extrusion was performed with a 50% reduction of area, and the temperature history in the punch was measured with a thermocouple. The forging speed was 1, 3, and 10 spm. FEM analysis was performed to simulate the experiment by considering the temperature dependence of flow stress and friction coefficient. The heat transfer coefficient was estimated at 20 kW/(m2•°C) by comparing the experimental result and calibration curves.